class_docstr: Base class for defining classification loss functions. Sub-classes must implement forward function.
  
  Args:
      opts: command line arguments
docstr: Sub-classes must override this function to compute loss
  
  Args:
      prediction: Output of the model
      target: ground truth
  
  Returns:
      Expected to return a scalar value of loss
docstr_tok: ["Sub-classes","must","override","this","function","to","compute","loss","Args",":","prediction",":","Output","of","the","model","target",":","ground","truth","Returns",":","Expected","to","return","a","scalar","value","of","loss"]
code: def _compute_loss(
      self, prediction: Tensor, target: Tensor, *args, **kwargs
  ) -> Tensor:
      """Sub-classes must override this function to compute loss
  
      Args:
          prediction: Output of the model
          target: ground truth
  
      Returns:
          Expected to return a scalar value of loss
      """
      raise NotImplementedError
  
file_path: ml-cvnets/loss_fn/classification/base_classification_criteria.py
imports: import argparse
  from typing import Any, Dict, Union
  from torch import Tensor
  from loss_fn import LOSS_REGISTRY, BaseCriteria
  from utils import logger
label_desc: Use image node_id 3 for calling the BaseClassificationCriteria obj's underlying member method code with example usage: obj._compute_loss(prediction, target) without return types